Acoustic reflection imaging in deep water wells is a new application scope for offshore hydrocarbon exploration.Two-dimensional(2 D)geological structure images can be obtained away from a one-dimensional(1 D)borehole ...Acoustic reflection imaging in deep water wells is a new application scope for offshore hydrocarbon exploration.Two-dimensional(2 D)geological structure images can be obtained away from a one-dimensional(1 D)borehole using single-well acoustic reflection imaging.Based on the directivity of dipole source and four-component dipole data,one can achieve the azimuth detection and the three-dimensional(3 D)structural information around the wellbore can be obtained.We first perform matrix rotation on the field fourcomponent data.Then,a series of processing steps are applied to the rotated dipole data to obtain the reflector image.According to the above dipole shear-wave imaging principle,we used four-component cross-dipole logging data from a deviated well in the South China Sea to image geological structures within 50 m of a deviated well,which can delineate the structural configuration and determine its orientation.The configuration of near-borehole bedding boundaries and fault structures from shear-wave imaging results agrees with those from the Inline and Xline seismic profiles of the study area.In addition,the configuration and orientation of the fault structure images are consistent with regional stress maps and the results of the borehole stress anisotropy analysis.Furthermore,the dip azimuth of the bedding boundary images was determined using borehole wall resistivity data.Results of this study indicate that integrating borehole acoustic reflection with seismic imaging not only fills the gap between the two measurement scales but also accurately delineates geological structures in the borehole vicinity.展开更多
Images created from measurements made by wireline microresistivity imaging tools have longitudinal gaps when the well circumference exceeds the total width of the pad-mounted electrode arrays.The gap size depends on t...Images created from measurements made by wireline microresistivity imaging tools have longitudinal gaps when the well circumference exceeds the total width of the pad-mounted electrode arrays.The gap size depends on the tool design and borehole size,and the null data in these gaps negatively aff ect the quantitative evaluation of reservoirs.Images with linear and texture features obtained from microresistivity image logs have distinct dual fabric features because of logging principles and various geological phenomena.Linear image features usually include phenomena such as fractures,bedding,and unconformities.Contrarily,texture-based image features usually indicate phenomena such as vugs and rock matrices.According to the characteristics of this fabric-based binary image structure and guided by the practice of geological interpretation,an adaptive inpainting method for the blank gaps in microresistivity image logs is proposed.For images with linear features,a sinusoidal tracking inpainting algorithm based on an evaluation of the validity and continuity of pixel sets is used.Contrarily,the most similar target transplantation algorithm is applied to texture-based images.The results obtained for measured electrical imaging data showed that the full borehole image obtained by the proposed method,whether it was a linear structural image refl ecting fracture and bedding or texture-based image refl ecting the matrix and pore of rock,had substantially good inpainting quality with enhanced visual connectivity.The proposed method was eff ective for inpainting electrical image logs with large gaps and high angle fractures with high heterogeneity.Moreover,ladder and block artifacts were rare,and the inpainting marks were not obvious.In addition,detailed full borehole images obtained by the proposed method will provide an essential basis for interpreting geological phenomena and reservoir parameters.展开更多
基金supported by the National Natural Science Foundation of China(Nos.41804124,41774138,41804121,41604109)China Academy of Sciences Strategic Leading Science and Technology Project(Grant Nos.XDA14020304,XDA14020302)+2 种基金Shandong Provincial Natural Science Foundation,China(No.ZR2019BD039)Shandong Province Postdoctoral Innovation Project(No.201901011)China Postdoctoral Science Foundation(Grant Nos.2019T120615,2018M632745)
文摘Acoustic reflection imaging in deep water wells is a new application scope for offshore hydrocarbon exploration.Two-dimensional(2 D)geological structure images can be obtained away from a one-dimensional(1 D)borehole using single-well acoustic reflection imaging.Based on the directivity of dipole source and four-component dipole data,one can achieve the azimuth detection and the three-dimensional(3 D)structural information around the wellbore can be obtained.We first perform matrix rotation on the field fourcomponent data.Then,a series of processing steps are applied to the rotated dipole data to obtain the reflector image.According to the above dipole shear-wave imaging principle,we used four-component cross-dipole logging data from a deviated well in the South China Sea to image geological structures within 50 m of a deviated well,which can delineate the structural configuration and determine its orientation.The configuration of near-borehole bedding boundaries and fault structures from shear-wave imaging results agrees with those from the Inline and Xline seismic profiles of the study area.In addition,the configuration and orientation of the fault structure images are consistent with regional stress maps and the results of the borehole stress anisotropy analysis.Furthermore,the dip azimuth of the bedding boundary images was determined using borehole wall resistivity data.Results of this study indicate that integrating borehole acoustic reflection with seismic imaging not only fills the gap between the two measurement scales but also accurately delineates geological structures in the borehole vicinity.
基金This work was supported by Initial Scientifi c Research Fund for Doctor of Xinjiang University(No.620321016)Gansu Provincial Natural Science Foundation of China(No.17JR5RA313)Key Laboratory of Petroleum Resource Research of Chinese Academy of Science Foundation(No.KFJJ2016-02).
文摘Images created from measurements made by wireline microresistivity imaging tools have longitudinal gaps when the well circumference exceeds the total width of the pad-mounted electrode arrays.The gap size depends on the tool design and borehole size,and the null data in these gaps negatively aff ect the quantitative evaluation of reservoirs.Images with linear and texture features obtained from microresistivity image logs have distinct dual fabric features because of logging principles and various geological phenomena.Linear image features usually include phenomena such as fractures,bedding,and unconformities.Contrarily,texture-based image features usually indicate phenomena such as vugs and rock matrices.According to the characteristics of this fabric-based binary image structure and guided by the practice of geological interpretation,an adaptive inpainting method for the blank gaps in microresistivity image logs is proposed.For images with linear features,a sinusoidal tracking inpainting algorithm based on an evaluation of the validity and continuity of pixel sets is used.Contrarily,the most similar target transplantation algorithm is applied to texture-based images.The results obtained for measured electrical imaging data showed that the full borehole image obtained by the proposed method,whether it was a linear structural image refl ecting fracture and bedding or texture-based image refl ecting the matrix and pore of rock,had substantially good inpainting quality with enhanced visual connectivity.The proposed method was eff ective for inpainting electrical image logs with large gaps and high angle fractures with high heterogeneity.Moreover,ladder and block artifacts were rare,and the inpainting marks were not obvious.In addition,detailed full borehole images obtained by the proposed method will provide an essential basis for interpreting geological phenomena and reservoir parameters.
